A pedestrian detection system for underground mine vehicles is being developed that requires the segmentation of people from thermal images in underground mine tunnels. A number of thresholding techniques are outlined and their performance on a number of thermal images is investigated. The thresholding techniques are evaluated on images in various ambient conditions and it is shown that a minimum error thresholding technique is the most effective.